作者:Zhang, Y (Zhang, Yi)^{[ 1 ]} ; Lyu, XQ (Lyu, Xiuqin)^{[ 2 ]}

JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING

卷: 17期: 1 文献号: 011010

DOI: 10.1115/1.4035000

出版年: MAR 2017

摘要

To improve the quality of point cloud data, as well as maintain edge and detail information in the course of filtering intensity data, a three-dimensional (3D) diffusion filtering equation based on the general principle of diffusion filtering is established in this paper. Moreover, we derive theoretical formulas for the scale parameter and maximum iteration number and achieve self-adaptive denoising, fine control of the point cloud filtering, and accurate prediction of the diffusion convergence. Through experiments with three types of typical point cloud intensity data, the theoretical formulas for the scale parameter and iteration number are verified. Comparative experiments with point cloud data of different types show that the 3D diffusion filtering method has significant denoising and edge-preserving abilities. Compared with the traditional median filtering algorithm, the signal-to-noise ratio (SNR) of the point cloud after filtering is increased by an average of 10% and above, with a maximum value of 40% and above.

关键词

作者关键词:laser scanning; point cloud intensity noise; 3D diffusion filtering; scale parameter; SNR

作者信息

通讯作者地址: Lyu, XQ (通讯作者)

地址:

电子邮件地址:yzhang@sgg.whu.edu.cn; winterlxq@sina.com

基金资助致谢

查看基金资助信息

出版商

ASME, TWO PARK AVE, NEW YORK, NY 10016-5990 USA

类别/分类

研究方向:Computer Science; Engineering

Web of Science类别:Computer Science, Interdisciplinary Applications; Engineering, Manufacturing

文献信息

文献类型:Article

语种:English

入藏号: WOS:000395505500011

ISSN: 1530-9827

eISSN: 1944-7078

期刊信息

· Impact Factor (影响因子): 0.790